Businesses and organizations strive to maximize the strategic value and operational efficiency of their IT infrastructure. Money invested in IT transformation needs to be clearly justified by the expected business advantage it will create. In a world of globally distributed and remotely managed IT systems, frequent mergers and acquisitions, and rapidly evolving business priorities, there is an increasing need to monitor, manage and analyze how business processes utilize IT resources in an integrated and timely manner. While solutions exist for monitoring IT resource utilization/performance or provisioning business process performance dashboards, the ability to dynamically associate IT service operations data across layers of business processes and value models, applications, and hardware infrastructure is not currently available.
Lacking a good means of monitoring and controlling instance-based cross-layer relationships limits an organization's ability to optimize its business performance. For example, minimizing IT operating cost by isolating, simplifying and/or transforming an IT system without compromising any user experience management standard at a business process level requires deep insights about dynamic cross-layer relationships. Prioritizing and reacting to IT infrastructure management incidents (e.g., server failure) based upon process-level key performance/risk indicators (KPIs/KRIs) or contractual service level agreements (SLAs) require analyzing dynamic instance-based relationships in a timely manner. Competitively reducing problem determination time for business process/transaction incidents can be done by exploiting the historical data on the cross-layer relationships.
However, it is non-trivial to discover dynamic cross-layer utilization relationships between the managed IT resources without the ability of accessing and changing the source code of the software in use. Such non-triviality can well be appreciated via a Service Oriented Architecture (SOA) based IT infrastructure, in which functional capabilities of every network-based distributed computing component can be externalized via one or more “service” interfaces such as, for example, the Web Services interfaces specified via Web Service Definition Language (WSDL). Business Process Execution Language (BPEL) based process choreography engines are usually used to codify, realize, and automate actionable business process flows and to dynamically orchestrate the execution of the service components.
It can be advantageous for the owner of a service oriented IT infrastructure to timely determine how a specific external Web Service invocation, issued by a customer, utilizes the managed networked servers in the infrastructure. For example, such utilization information may enable the owner to competitively leverage IT in business terms.
Web Service invocations can be monitored by contemporary IT monitoring/metering products such as, for example, IBM Tivoli Composition Application Monitor for SOA (ITCAM for SOA). The runtime status of all of the process choreography entities can be obtained via contemporary middleware products, such as, for example, IBM WebSphere Process Server (WPS). However, the owner cannot easily determine (or discover) the utilization relationships between the Web Service invocations and the managed servers.
Monitoring and metering data are logged at various levels and at different machines. It is non-trivial to get an integrated view of all the relevant data due to the lack of standards on how to correlate those data. For example, there are no standards in correlating the relationships between BPEL workflow execution entities, Web Service invocations, and server CPU utilization data.
In addition, data is formatted differently by different tools. There are no standards on the needed monitoring data in terms of format and semantics. For example, each WPS CBE (Common Base Event) event is an XML-formatted message, whereas each ITCAM for SOA log entry is a delimiter-separated text line.
Further, the same type of monitoring data can be captured by different monitoring applications, and each from different perspectives. For example, both ITCAM for SOA log files and WPS CBE events can provide information on SCA (Service Component Architecture) invocations, but the tools format the invocation monitoring data differently with different details. Each CBE event emitted from a specific WPS server relates to a lifecycle state change of an SCA invocation that happened on that server. However, ITCAM for SOA generates SCA invocation monitoring data from both the caller and the callee perspectives. There are two log entries for each lifecycle state change of an SCA invocation one for the caller, and the other for the callee. ITCAM for SOA also performs the monitoring with the goal of linking related SCA and Web Service invocations.
Moreover, the relationship determination process must be as non-intrusive as possible. The owner cannot rely on making source code changes to the managed applications and middleware for the needed relationship discovery and analysis data. The owner can only infer from the data provided by the deployed monitoring applications.
Conventional practices of realizing business-aligned management of shared IT infrastructures rely on ad hoc exploitation of the target system's component configuration files, application execution logs, and monitoring/metering data relationships. Conventional IT monitoring/metering products, such as, for example, BMC Patrol, HP OpenView and IBM Tivoli Monitor, can be used to gather detailed availability, performance, and utilization load data for each individual IT resource. Contemporary Business Service Management (BSM) products, such as, for example, CA eHealth, IBM Tivoli BSM and Proxima Centauri, support quality incident propagation through layered business system components via component dependency models. For example, a disk failure may impact the availability of a database application server which belongs to a particular line of business.
However, none of these products were developed to manage the dynamic execution dependency and resource consumption relationships between business process transaction instances and the underlying IT resources. It is also non-trivial to leverage those contemporary IT management products'capabilities in providing the desired visibility of instance-based dynamic utilization relationships between IT resources at layers of processes, applications, and servers.
U.S. Patent Application Publication US20060129419 proposes a method for progressively deriving the deployment configuration architecture of an IT system with the goal of minimizing the IT cost to value ratio for a given set of business functions. The method also provides an automatic means of coupling a component based model (CBM) of a business to components of an IT entity model, which uses the notion of “IT entity” to describe an IT system and environment. Besides IT entities, the base IT entity model comprises relationships among the IT entities and the interfaces and methods provided by these IT entities. The Publication teaches how to model, design, and analyze a “static” IT deployment architecture based upon cost to value ratio formulism and a component model of desired business functions. However, there is neither discussion about determining and analyzing “dynamic” utilization relationships between individual business process instances and IT infrastructure resources, nor the dynamic relationships between business and IT key performance indicators (KPIs). The Publication assumes the existence of a component-based model of business functions, a component-based model of IT assets, and the IT deployment alternatives between individual functional business components and sets of compositional IT assets. Timestamps are used to support the execution of an IT configuration derivation system before the IT system is deployed, but not to record the runtime behavior of deployed IT resources.
U.S. Patents Application Publications US20050119905, US20050125768, and US20050125449 disclose modeling of applications and business process services through auto discovery analysis, with static business process models (as proxies for real, executing business processes) interfaced to a common computing and management environment. However, the Publications do not include details on the information model used for modeling IT infrastructure components, business processes, and the dynamic utilization relationships between them. The information model covered in the Publications is similar to the object dependency models supported by contemporary BSM products such as, for example, CA eHealth, IBM TBSM, and Proxima Centauri. All of the models enable template-based grouping of IT infrastructure components and their KPIs into hierarchical “dependency topology” maps, each of which has a business function (or a business process solution identity) as its root. The maps are the basis for the business relevant IT management proposed in the Publications.
However, the Publications neither teach how to discover the dependency relationships between all of the IT infrastructure components (at layers of networked servers, applications, and process workflows) during the execution of a specific business process instance, nor the necessary information model for storing, analyzing, and exploiting those dynamic cross-layer utilization dependency data across all business process execution transactions.
U.S. Patent Application Publication US20050096949 proposes a mathematical model based adaptive approach to continuously manage the IT infrastructure configuration settings based upon business objectives. However, the publication neither teaches how to quantitatively validate the needed mathematical models using real measurement data in practice, nor how to effectively maintain the models for a changing IT infrastructure.
U.S. Pat. No. 6,976,090 proposes an Internet-based decentralized and differentiated content/application delivery solution, which enables content providers to directly control the delivery of content based upon regional and temporal preferences, client identity, and content priority. The patent teaches how decisions on content placement and replication can be controlled by a policy enactment scheme and how user requests to the contents can be routed to the most appropriate server based on the content providers' content delivery policies. However the publication does not teach how to discover, analyze, or exploit cross-layer utilization relationships between business transactions and IT infrastructure components.
Conventional methods have also been proposed to perform timestamp-base correlation between received messages and sent messages based on network-level traffic monitoring data. While these methods may discover network-protocol based relationships, they do not teach how to integrate the relationships with other inter-resource utilization relationships, such as those between business process level resources and application level resources, to discover the end-to-end business-IT utilization relationships.
Thus, there is a need for a system and method that can determine the resources generated by a service request by discovering dynamic utilization relationships between managed IT resources at the same or different IT layers using the data gathered by all of the deployed monitoring applications.